AI Use Cases & Concepts for Salesforce Professionals

Learn what Artificial Intelligence (AI) means, how it works by processing data and learning patterns, and how it's used in real life—from Siri to Netflix recommendations.

Terms Covered:
Artificial Intelligence (AI), Human-like Intelligence, Data Processing, Pattern Recognition, Predictions, Recommendation Systems

Trace the journey of AI from rule-based automation to autonomous AI agents. Learn how Salesforce tools like Workflow Rules, Einstein GPT, and Agentforce reflect this evolution in real-world automation.

Terms Covered:
Rule-Based AI, Workflow Rules, Machine Learning (ML), Einstein Prediction Builder, Generative AI, Einstein GPT, Prompt Builder, Autonomous Agents, Agentforce

Explore the three major types of AI—Narrow, General, and Super AI—and understand key domains like NLP, Computer Vision, and Robotics through real-world examples.

Terms Covered:
Narrow AI, General AI, Super AI, Natural Language Processing (NLP), Computer Vision, Robotics

Discover how Natural Language Processing (NLP) helps AI understand and respond to human language. See how Salesforce uses NLP in Einstein GPT for Service to automate smarter customer interactions.

Terms Covered:
Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Einstein GPT for Service, AI-Powered Responses

Discover how Computer Vision enables machines to understand visual data, and see how Salesforce uses Einstein Vision to extract text from invoices, receipts, and scanned documents automatically.

Terms Covered:
Computer Vision, Image Processing, Text Extraction, Einstein Vision, Invoice Scanning, Document Automation

Explore how robotics and AI work together to automate tasks, boost precision, and transform industries—from warehouses and farms to smart homes and hospitals.

Terms Covered:
Robotics, Smart Automation, AI-Powered Robots, Sensing-Processing-Acting Cycle, Warehouse Robots, Robot Vacuums, Autonomous Machines

Learn how AI systems learn using Supervised, Unsupervised, and Reinforcement Learning. See how Salesforce applies these methods in tools like Einstein Prediction Builder and Einstein Discovery to drive smarter business decisions.

Terms Covered:
Supervised Learning, Unsupervised Learning, Reinforcement Learning, Einstein Prediction Builder, Einstein Discovery, AI Model Training

Explore how Artificial Neural Networks and Deep Learning power advanced AI capabilities like image recognition and predictive insights. Learn how Salesforce uses Deep Learning in Einstein Vision for text extraction from images and documents.

Terms Covered:
Artificial Neural Networks (ANN), Deep Learning, Neural Network Layers, Input-Hidden-Output, Einstein Vision, Image Recognition, Text Extraction

Explore how Generative AI creates original content like text, images, and music using learned patterns. Learn about its applications, how it works, and the real-world challenges it presents.

Terms Covered:
Generative AI, Foundation Models (FMs), Generator, Discriminator, GANs, Content Creation, AI Hallucinations, AI Bias, Real-World Applications

Explore how GPT (Generative Pre-trained Transformer) works as a Large Language Model, powering tools that generate text, support customers, and write code. Learn its core components, strengths, and real-world applications.

Terms Covered:
GPT, Large Language Model (LLM), Generative Pre-trained Transformer, Tokens, Embeddings, Transformers, Content Generation, AI Hallucinations

Discover how Conversational AI powers natural, human-like interactions through chatbots, virtual assistants, and smart devices. Learn how technologies like NLP, ML, and Speech Recognition make conversations with machines smoother and smarter.

Terms Covered:
Conversational AI, Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Speech Recognition, Text-to-Speech (TTS), Chatbots, Virtual Assistants

Learn how Sentiment Analysis helps AI understand human emotions in text—from reviews to support tickets. Discover the techniques, real-world applications, and challenges, including how Salesforce integrates sentiment insights for smarter decisions.

Terms Covered:
Sentiment Analysis, Natural Language Processing (NLP), Sentiment Score, Tokenization, Rule-Based Approach, Machine Learning, Sarcasm Detection, Emotion Detection, Salesforce Sentiment Tracking

Learn how Parameters and Transformers work behind the scenes in modern AI models. Discover how parameters help AI understand language and how the Transformer architecture powers tools like chatbots, translators, and content generators.

Terms Covered:
AI Parameters, Transformer Architecture, Attention Mechanism, Token Embeddings, GPT, Language Processing, AI Model Training, Computational Cost, Bias in AI

Learn how Augmented Intelligence empowers humans by combining AI insights with human decision-making. Discover how this human-AI partnership improves efficiency, creativity, and strategic thinking across industries.

Terms Covered:
Augmented Intelligence, Human-AI Collaboration, AI-Assisted Decision-Making, Human-in-the-Loop, Real-Time Insights, AI Empowerment, Salesforce AI Tools

Learn how AI inference parameters—Temperature, Top-p, and Top-k—shape the creativity, focus, and variation in text generated by models like GPT. Understand how to fine-tune these settings for different use cases like chatbots, storytelling, and code generation.

Terms Covered:
Inference Parameters, Temperature, Top-p (Nucleus Sampling), Top-k, Generative AI Output Control, GPT Settings, Creativity in AI, AI Response Tuning

Explore how Generative Adversarial Networks (GANs) work using two neural networks—Generator and Discriminator—in a feedback loop. Learn their real-world applications in image generation, data augmentation, and creative content, along with key benefits and ethical challenges.

Terms Covered:
Generative Adversarial Networks (GANs), Generator, Discriminator, Feedback Loop, DeepFakes, Style Transfer, Data Augmentation, Training Instability, Mode Collapse

Discover how the Generator drives content creation in Generative AI systems. Learn how it transforms prompts and patterns into text, images, music, and more—fueling creativity across industries.

Terms Covered:
Generator, Generative AI, Content Creation, Pattern Matching, GANs, AI Creativity, AI Art, AI Writing, AI Music, AI Challenges

Understand how the Discriminator in a Generative Adversarial Network (GAN) evaluates AI-generated content to determine if it’s real or fake. Learn how it helps improve AI output quality through a feedback loop with the Generator.

Terms Covered:
Discriminator, Generator, GANs, Feedback Loop, Real vs. Fake Detection, Mode Collapse, Overfitting, Quality Control in AI

Understand what AI hallucinations are—when AI confidently generates false or misleading information. Learn why they happen, how they impact critical decisions, and how to reduce them with better training, prompts, and human oversight.

Terms Covered:
AI Hallucination, Misinformation in AI, Training Data Gaps, Fine-Tuning, Human-AI Collaboration, AI Confidence Scores, AI Output Validation

Explore the core of every AI system—the AI Model. Learn how models are built, what they do, and the different types used for prediction, classification, generation, and recommendations. Discover how models are evaluated, fine-tuned, and applied in the real world.

Terms Covered:
AI Model, Model Training, Parameters, Regression, Classification, Generative Model, Recommendation System, Model Evaluation, Accuracy, Overfitting, Bias in AI

Learn how to craft clear, structured prompts to get accurate, focused responses from AI. Discover key ingredients, techniques like Chain-of-Thought and Role-Based prompting, common mistakes to avoid, and real-world applications in customer service, content creation, and more.

Terms Covered:
Prompt Engineering, Chain-of-Thought Prompting, Zero-Shot, Few-Shot, Role-Based Prompting, Prompt Structure, Effective AI Prompts, AI Output Quality

Discover how Foundation Models serve as the base for a wide range of AI applications—from chatbots and content generation to medical analysis. Learn how they're built, fine-tuned, and applied across industries, along with their benefits, challenges, and future trends.

Terms Covered:
Foundation Models, Pre-Training, Fine-Tuning, GPT, DALL-E, BERT, Stable Diffusion, Multimodal AI, Scalable AI, Generative AI, AI Model Adaptability

Learn how Retrieval-Augmented Generation (RAG) enhances AI by combining real-time information retrieval with text generation. Discover how it enables AI to produce more accurate, up-to-date responses in customer service, healthcare, finance, and beyond.

Terms Covered:
Retrieval-Augmented Generation (RAG), Real-Time AI, Knowledge Retrieval, Text Generation, RAG in Chatbots, AI Hallucination Reduction, Live Data Integration

Learn how AI models are tested, compared, and validated using metrics like accuracy, precision, and F1 score. Explore how benchmarking ensures fairness, highlights performance leaders, and guides data-driven decisions in AI development.

Terms Covered:
Model Evaluation, AI Benchmarking, Accuracy, Precision, Recall, F1 Score, AUC-ROC, Overfitting, Standard Datasets, Explainability, Continuous Evaluation

Explore how AI understands and represents language by breaking down input into tokens, turning them into embeddings, and analyzing them as vectors. Learn how these components work together to power chatbots, recommendation engines, search systems, and more.

Terms Covered:
Tokens, Embeddings, Vectors, Tokenization, AI Representation, Multi-Dimensional Space, Word Similarity in AI, Vector Embedding, AI Understanding Language